109 citations · 315 across the 34 of their papers we have counts for
35 papers
DiffusionEngine: Diffusion Model is Scalable Data Engine for Object Detection
Manlin Zhang, Jie Wu, Yuxi Ren +7
Data is the cornerstone of deep learning. This paper reveals that the recently developed Diffusion Model is a scalable data engine for object detection. Existing methods for scalin…
Master-slave Deep Architecture for Top-K Multi-armed Bandits with Non-linear Bandit Feedback and Diversity Constraints
Hanchi Huang, Li Shen, Deheng Ye +1
We propose a novel master-slave architecture to solve the top- combinatorial multi-armed bandits problem with non-linear bandit feedback and diversity constraints, which, to the…
Fritz-John optimality condition in fuzzy optimization problems and its application to classification of fuzzy data
Fangfang Shi, Guoju Ye, Wei Liu +1
The main objective of this paper is to derive the optimality conditions for one type of fuzzy optimization problems. At the beginning, we define a cone of descent direction for fuz…
Global and Local Semantic Completion Learning for Vision-Language Pre-training
Rong-Cheng Tu, Yatai Ji, Jie Jiang +6
Cross-modal alignment plays a crucial role in vision-language pre-training (VLP) models, enabling them to capture meaningful associations across different modalities. For this purp…
GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions
Tao Wang, Kaihao Zhang, Ziqian Shao +6
Image restoration in adverse weather conditions is a difficult task in computer vision. In this paper, we propose a novel transformer-based framework called GridFormer which serves…
CFFT-GAN: Cross-domain Feature Fusion Transformer for Exemplar-based Image Translation
Tianxiang Ma, Bingchuan Li, Wei Liu +3
Exemplar-based image translation refers to the task of generating images with the desired style, while conditioning on certain input image. Most of the current methods learn the co…
Quantitative mean ergodic inequalities: power bounded operators acting on one single noncommutative space
Guixiang Hong, Wei Liu, Bang Xu
In this paper, we establish the quantitative mean ergodic theorems for two subclasses of power bounded operators on a fixed noncommutative -space with , which main…
Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation
Jie Jiang, Zhimin Li, Jiangfeng Xiong +3
Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failin…
A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications
Can Li, Lei Bai, Lina Yao +2
Transportation is the backbone of the economy and urban development. Improving the efficiency, sustainability, resilience, and intelligence of transportation systems is critical an…
CircuitNet: An Open-Source Dataset for Machine Learning Applications in Electronic Design Automation (EDA)
Zhuomin Chai, Yuxiang Zhao, Yibo Lin +3
The electronic design automation (EDA) community has been actively exploring machine learning (ML) for very large-scale integrated computer-aided design (VLSI CAD). Many studies ex…
Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task
Stan Weixian Lei, Difei Gao, Jay Zhangjie Wu +4
VQA is an ambitious task aiming to answer any image-related question. However, in reality, it is hard to build such a system once for all since the needs of users are continuously…
SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
Zhihui Lin, Tianyu Yang, Maomao Li +4
Matching-based methods, especially those based on space-time memory, are significantly ahead of other solutions in semi-supervised video object segmentation (VOS). However, continu…
Unsupervised Knowledge Adaptation for Passenger Demand Forecasting
Can Li, Lei Bai, Wei Liu +2
Considering the multimodal nature of transport systems and potential cross-modal correlations, there is a growing trend of enhancing demand forecasting accuracy by learning from mu…
Tencent Text-Video Retrieval: Hierarchical Cross-Modal Interactions with Multi-Level Representations
Jie Jiang, Shaobo Min, Weijie Kong +4
Text-Video Retrieval plays an important role in multi-modal understanding and has attracted increasing attention in recent years. Most existing methods focus on constructing contra…
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution
Han Huang, Li Shen, Chaoyang He +2
Single Image Super-Resolution (SISR) tasks have achieved significant performance with deep neural networks. However, the large number of parameters in CNN-based met-hods for SISR t…
CPTR: Full Transformer Network for Image Captioning
Wei Liu, Sihan Chen, Longteng Guo +2
In this paper, we consider the image captioning task from a new sequence-to-sequence prediction perspective and propose CaPtion TransformeR (CPTR) which takes the sequentialized ra…
Global-Local Propagation Network for RGB-D Semantic Segmentation
Sihan Chen, Xinxin Zhu, Wei Liu +2
Depth information matters in RGB-D semantic segmentation task for providing additional geometric information to color images. Most existing methods exploit a multi-stage fusion str…
Defense-friendly Images in Adversarial Attacks: Dataset and Metrics for Perturbation Difficulty
Camilo Pestana, Wei Liu, David Glance +1
Dataset bias is a problem in adversarial machine learning, especially in the evaluation of defenses. An adversarial attack or defense algorithm may show better results on the repor…
Real-time Universal Style Transfer on High-resolution Images via Zero-channel Pruning
Jie An, Tao Li, Haozhi Huang +6
Extracting effective deep features to represent content and style information is the key to universal style transfer. Most existing algorithms use VGG19 as the feature extractor, w…
Energy Efficient User Clustering, Hybrid Precoding and Power Optimization in Terahertz MIMO-NOMA Systems
Haijun Zhang, Haisen Zhang, Wei liu +3
Terahertz (THz) band communication has been widely studied to meet the future demand for ultra-high capacity. In addition, multi-input multi-output (MIMO) technique and non-orthogo…
Knowledge-guided Deep Reinforcement Learning for Interactive Recommendation
Xiaocong Chen, Chaoran Huang, Lina Yao +3
Interactive recommendation aims to learn from dynamic interactions between items and users to achieve responsiveness and accuracy. Reinforcement learning is inherently advantageous…
Quantized Adam with Error Feedback
Congliang Chen, Li Shen, Haozhi Huang +1
In this paper, we present a distributed variant of adaptive stochastic gradient method for training deep neural networks in the parameter-server model. To reduce the communication…
Progressive Multi-Stage Learning for Discriminative Tracking
Weichao Li, Xi Li, Omar Elfarouk Bourahla +5
Visual tracking is typically solved as a discriminative learning problem that usually requires high-quality samples for online model adaptation. It is a critical and challenging pr…
MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
Yuan Gao, Haoping Bai, Zequn Jie +3
We propose to incorporate neural architecture search (NAS) into general-purpose multi-task learning (GP-MTL). Existing NAS methods typically define different search spaces accordin…